Institute of Smart Systems and Artificial Intelligence is looking for MLOps Engineer.
Responsibility:
– Deploying, monitoring, and maintaining machine learning models in production
environments;
– Working closely with data scientists;
– Ensuring seamless integration of machine learning models into operational
workflows;
– Managing GitHub and Hugging Face repositories (datasets, models, and
spaces).
Required skills and experience:
– At least 2 years of experience in MLOps, DevOps or a related field;
– At least Bachelor’s degree in Computer Science, Data Science or a related
field;
– Proficiency in Linux based operating systems;
– Strong understanding of machine learning principles and model lifecycle
management;
– Proficiency in programming languages such as Python, with hands-on
experience in machine learning frameworks like TensorFlow, PyTorch, or
Scikit-learn;
– Experience with working on the Hugging Face platform;
– Knowledge of CI/CD pipelines, automation tools and version control
systems like Git;
– Familiarity with containerization and orchestration tools such as Docker
and Kubernetes;
– Experience with monitoring tools and practices for model performance in
production (WandB, Tensorboard);
– Ability to work collaboratively in cross-functional teams;
– Knowledge of SQL would be a plus;
– Experience with cloud platforms like AWS, Azure, or Google Cloud and
their respective machine learning services would be a plus.